适度
风险厌恶(心理学)
背景(考古学)
结构方程建模
价值(数学)
抗性(生态学)
计算机科学
考试(生物学)
知识管理
营销
算法
经济
业务
机器学习
生态学
期望效用假设
数理经济学
生物
古生物学
作者
Hasan Mahmud,A. K. M. Najmul Islam,Ranjan Kumar Mitra
标识
DOI:10.1016/j.techfore.2023.122641
摘要
Artificial intelligence has been increasingly used in many managerial decision-making contexts for its superior performance. However, many managers are still averse to using AI algorithms in decision-making. The benefits of algorithms cannot be realized optimally if managers are reluctant to use them. Although there are many studies investigating the factors that make an individual averse towards algorithms, studies examining such factors in the managerial decision-making context are scarce. This study, drawing on the innovation resistance theory and the technology readiness concept, proposes a structural model depicting relationships between managers' perceived barriers and algorithm aversion. The model also incorporates the role of managers' technology readiness in influencing these relationships. To test the model, data were collected from 179 managers of 31 banks/financial institutions in Bangladesh through an online survey and were analyzed using partial least squares structural equation modeling. The results indicate that barriers related to value, tradition, and image are significantly associated with algorithm aversion, whereas barriers related to usage and risk have a non-significant impact. Moderation analysis suggests that motivating factors of technology readiness mitigate the impact of value barriers on algorithm aversion.
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